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Model: MorphMind-AI/CFM-Methods-7B
Source: Original Platform

.gitattributes

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LICENSE

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+MorphMind CFM Research License (v1.0)
+=====================================
+
+Copyright (c) 2026 MorphMind, Inc. All rights reserved.
+
+This model, "CFM-Methods-7B" (the "Model"), comprising its weights, configuration,
+and accompanying files, is released by MorphMind, Inc. ("MorphMind") for research
+and non-commercial use under the terms below.
+
+1. BASE MODEL.
+   The Model is a fine-tune of Qwen2.5-7B-Instruct, which is licensed by Alibaba
+   Cloud under the Apache License, Version 2.0. That permissive license is retained
+   for the underlying base, and use of the Model must preserve attribution to Qwen.
+   A copy of the Apache 2.0 license is available at
+   https://www.apache.org/licenses/LICENSE-2.0 .
+
+2. GRANT (RESEARCH / NON-COMMERCIAL).
+   Subject to these terms, MorphMind grants you a worldwide, non-exclusive,
+   royalty-free, non-transferable license to use, reproduce, and create derivative
+   works of the Model for research and other non-commercial purposes.
+
+3. ATTRIBUTION.
+   Any use, publication, or derivative must credit both "MorphMind CFM-Methods-7B"
+   and the "Qwen2.5" base model.
+
+4. COMMERCIAL USE.
+   Commercial use of the MorphMind fine-tuned weights is reserved. For a commercial
+   license, contact MorphMind at https://morphmind.ai .
+
+5. INTENDED USE & DISCLAIMER.
+   The Model is a high-recall screening tool, not a proof of correctness. It is
+   provided "AS IS", without warranty of any kind. MorphMind is not liable for any
+   decision made in reliance on the Model's output. Keep a qualified human in the loop.
+
+6. RESPONSIBLE USE.
+   Do not use the Model to misrepresent machine-generated review as human review in
+   any setting where that distinction is required by law, policy, or contract.

README.md

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+---
+license: other
+license_name: morphmind-cfm-research-license
+license_link: LICENSE
+base_model: Qwen/Qwen2.5-7B-Instruct
+pipeline_tag: text-generation
+library_name: transformers
+inference: false
+tags:
+- control-foundation-model
+- scientific-ai
+- methodology-review
+- peer-review
+- rlvr
+- morphmind
+---
+
+# CFM-Methods-7B · MorphMind
+
+**A control model that reads a methods section and flags where the methodology is unsound.** Give it a
+methods or experimental-design block from any empirical-science paper — **statistics, machine learning,
+quantitative biology, econometrics, materials science, or chemical physics** — and it returns a
+structured verdict, **support** or **refute**, pinpoints the offending statement, and explains why. It is
+a **high-recall screen**: it surfaces methodological red flags — data leakage, p-hacking, uncorrected
+multiple comparisons, train/test contamination, optional stopping, correlation-as-causation, post-hoc
+outlier removal, unblinded scoring, and more — so a human misses almost nothing.
+
+CFM-Methods-7B is the **conformance pillar** of MorphMind's **Control Foundation Model (CFM)** line —
+models whose job is not to *generate* science but to **check** it.
+
+*By [MorphMind](https://morphmind.ai). Research preview.*
+
+## Benchmark — methodology-flaw detection (honest, held-out)
+
+![methodology benchmark](benchmark.png)
+
+Evaluated on **flaw types the model never trained on** (24 flaw families used for training, **12 held
+out for evaluation**) — so this measures *generalization*, not memorization — and benchmarked head-to-head
+against frontier models on the **same held-out set**:
+
+| Model | Recall | Precision | Localization | False-positive rate (clean) |
+|---|---|---|---|---|
+| base Qwen2.5-7B | 0.30 | — | 0.42 | 0.07 |
+| GPT-4o | 0.86 | 0.64 | 0.94 | 0.47 |
+| Claude Opus 4 | 0.96 | 0.78 | 0.97 | 0.28 |
+| **CFM-Methods-7B (ours)** | **0.98** | **1.00** | **0.98** | **0.00** |
+
+**CFM-Methods-7B leads on recall and localization — and is the only model with zero false alarms.** It
+catches 98% of methodological flaws it has never seen and pinpoints the exact flawed statement 98% of the
+time, ahead of Claude Opus 4, while the frontier models over-flag clean methods heavily (Opus 28%, GPT-4o
+47% false-positive rate). So it delivers **frontier-leading methodology screening with the precision of a
+careful expert — on-prem, at ~1/100 the cost of a frontier API**, and can run across every methods
+section in your pipeline. Recall stays high across all 12 held-out flaw families; a human makes the final
+call.
+
+## Worked example
+
+**1 — it catches an uncorrected multiple-comparisons flaw.** Given this methods block:
+
+> *"We screened 60 candidate protein markers for association with disease status. Each marker was
+> tested individually with a univariate logistic regression at the 0.05 level. The 14 markers reaching
+> p < 0.05 in univariate tests are reported as significant and carried forward as the disease signature."*
+
+CFM-Methods-7B returns (verbatim model output):
+
+```json
+{
+  "analysis": "There is a multiple testing problem: 14 out of 60 tests reaching p < 0.05 by chance alone.",
+  "verdict": "refute",
+  "error_spans": [
+    {
+      "text": "Each marker was tested individually with a univariate logistic regression at the 0.05 level.",
+      "why": "There is a multiple testing problem: 14 out of 60 tests reaching p < 0.05 by chance alone."
+    }
+  ],
+  "action": "suggest_edit"
+}
+```
+
+It pinpoints the offending sentence and quantifies the failure — 60 simultaneous tests at α = 0.05 with
+no correction.
+
+**2 — and it passes clean methods without crying wolf.** Given a sound instrumental-variables design:
+
+> *"We estimate the causal effect of schooling on wages with two-stage least squares, instrumenting
+> years of education with quarter-of-birth. We report first-stage F-statistics to confirm instrument
+> strength and cluster standard errors at the state level."*
+
+```json
+{
+  "analysis": "The methods are sound — the analysis choices are appropriate for the data and claims.",
+  "verdict": "support",
+  "error_spans": [],
+  "action": "accept"
+}
+```
+
+No false flag — the zero false-positive rate in the benchmark above is what this looks like in practice.
+
+## When & how to use it
+Use it as a **fast first-pass methodology screen** — to flag questionable analysis choices before a
+human deep-read, to triage submissions, or to vet AI-generated methods. **Review one methods block at a
+time** (split a paper into its method/experiment/analysis sections and run each). Because it is tuned
+for recall, treat its flags as *"worth a human's 30 seconds."* Keep a human in the loop.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+tok = AutoTokenizer.from_pretrained("MorphMind-AI/CFM-Methods-7B")
+model = AutoModelForCausalLM.from_pretrained("MorphMind-AI/CFM-Methods-7B",
+                                             torch_dtype=torch.bfloat16, device_map="auto")
+SYS = ("You are a scientific methodology reviewer. Review the methods and respond ONLY with JSON: "
+       "{\"analysis\":...,\"verdict\":\"support|refute\","
+       "\"error_spans\":[{\"text\":...,\"why\":...}],\"action\":\"accept|suggest_edit\"}")
+def review(methods):
+    msgs=[{"role":"system","content":SYS},{"role":"user","content":"METHODS:\n"+methods}]
+    ids=tok.apply_chat_template(msgs, add_generation_prompt=True, return_tensors="pt").to(model.device)
+    out=model.generate(ids, max_new_tokens=320, do_sample=False)
+    return tok.decode(out[0, ids.shape[1]:], skip_special_tokens=True)
+```
+
+## How it was built
+A full-parameter fine-tune of Qwen2.5-7B-Instruct, trained with **RLVR** (Reinforcement Learning from
+Verifiable Rewards) under a **localization-gated reward** — a verdict is reinforced only if the model
+also points to the actual flawed statement, which forces real reasoning rather than blanket "refute."
+Trained on public **arXiv** methods sections (statistics, ML, quantitative biology, econometrics,
+materials science, chemical physics) with injected, paraphrased methodological flaws.
+
+## Notes
+- A **high-recall screen** built for first-pass review: it surfaces ~98% of methodological flaws so a
+  human misses almost nothing, with a near-zero false-alarm rate — designed to keep an expert in the loop
+  for the final call.
+- **Generalizes** strongly to methodological flaws it has never seen, across statistics, ML, biology,
+  econometrics, materials science, and chemistry.
+- Part of MorphMind's growing **Control Foundation Model** family — research preview, improving with
+  every release.
+
+## License
+Released under the **MorphMind CFM Research License** (see `LICENSE`). The Qwen2.5-7B base is Apache-2.0;
+this fine-tune is for **research / non-commercial** use, attribution to MorphMind and Qwen.
+**Commercial licensing: contact MorphMind (morphmind.ai).**

added_tokens.json

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chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": 131072,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.52.4",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

generation_config.json

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+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.52.4"
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